{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 条形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7fdb215e10f0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(12345)\n",
    "x = np.arange(5)\n",
    "y = np.random.randint(-5, 5, 5)\n",
    "fig, axes = plt.subplots(ncols=2)\n",
    "v_bars = axes[0].bar(x,y,color='red')\n",
    "h_bars = axes[1].barh(x,y,color='red')\n",
    "\n",
    "axes[0].axhline(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "v_vars = ax.bar(x,y)\n",
    "for bar, height in zip(v_vars, y):\n",
    "    if height < 0:\n",
    "        bar.set(edgecolor = 'darkred', color = 'green', linewidth=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.randn(100).cumsum()\n",
    "y = np.linspace(0,10,100)\n",
    "fig, ax = plt.subplots()\n",
    "ax.fill_between(x,y,color='lightblue')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 条形图细节"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mean_values = [1,2,3]\n",
    "variance = [0.2, 0.4, 0.5]\n",
    "bar_label = ['bar1', 'bar2', 'bar3']\n",
    "x_pos = list(range(len(bar_label)))\n",
    "\n",
    "plt.bar(x_pos, mean_values, yerr=variance) #柱状图上面加条杠\n",
    "max_y = max(zip(mean_values, variance))\n",
    "plt.xticks(x_pos, bar_label) #修改x轴\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
